Signal & Noise

What happens when artificial intelligence stops being just another productivity tool—and starts changing how we think about work, creativity, organizations, and even what it means to be human?In this thought-provoking episode of Signal & Noise, hosts Rio Longacre and Brett House sit down with entrepreneur and AI infrastructure founder Kyle Csik, Founder & CEO of Adaly AI, for a wide-ranging conversation that stretches from enterprise AI architecture to philosophy, economics, education, and the future of civilization. Kyle’s career has always sat at the intersection of technology, entrepreneurship, and systems thinking. After founding his first company at just 18 years old, he went on to build a career across programmatic advertising, retail media, and enterprise technology before launching Adaly AI, a company rethinking how organizations connect and reason across their data without relying on traditional data warehouses.But this conversation goes far beyond software.Inspired by Rio’s essay Machines of Loving Grace?—itself influenced by Anthropic CEO Dario Amodei’s optimistic vision for AI and E.M. Forster’s prophetic 1909 short story The Machine Stops—the discussion explores one of the biggest questions facing society:Is artificial intelligence simply another technology cycle… or is it fundamentally changing what it means to be human?Kyle argues that today’s large language models are incredibly powerful prediction engines—but they are not conscious, autonomous beings. Instead, their greatest value comes from augmenting human judgment, eliminating repetitive work, and freeing people to focus on creativity, relationships, and higher-order thinking.Along the way, the conversation dives into:Why today’s AI models are extraordinary prediction systems—but not artificial general intelligenceWhether humans are simply sophisticated prediction machines ourselvesHow every major technology—from writing to the internet—changed the skills humans needed to surviveWhy AI should augment human judgment rather than replace itThe surprising productivity gains Kyle has achieved by building personal AI agents into his everyday lifeWhy freeing people from administrative work could lead to stronger families, better education, and more creativityThe future of enterprise AI and why today’s data infrastructure is holding organizations backWhy Kyle believes traditional data warehouses represent an outdated computing model dating back to the 1960sHow federated AI architectures could fundamentally change how businesses access knowledgeWhy context—not simply bigger models—is becoming AI’s greatest competitive advantageHow AI could flatten organizational hierarchies while making companies dramatically more customer-centricThe evolution of SaaS, enterprise software, and agentic workflowsWhy CIOs remain frustrated despite massive enterprise AI investmentsThe growing disconnect between AI hype and practical implementation inside large organizationsThe risks of token-based AI pricing and enterprise vendor lock-inOpen-source AI versus frontier models—and why many Fortune 500 companies are choosing differently than expectedAI’s impact on education, scientific discovery, and innovationData centers, energy infrastructure, nuclear power, and the coming compute economySpace-based computing, Dyson spheres, and what it might take for civilization to become truly AI-poweredThe balance between government regulation, private innovation, and maintaining competitive marketsWhy the biggest challenge may not be artificial intelligence—but ensuring humans continue to develop wisdom, curiosity, and judgmentIt’s an expansive conversation that blends practical enterprise strategy with philosophy, economics, and the long-term future of technology—exactly the kind of discussion that sits at the heart of Signal & Noise.Connect with Kyle CsikLinkedIn: https://www.linkedin.com/in/kylecsik/Adaly AI: https://adaly.ai/

Gaming has grown far beyond entertainment. It is now one of the world’s largest industries—and one of technology’s most influential laboratories for understanding engagement, retention, monetization, community, and consumer behavior.In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Phylicia Koh, General Partner at Play Ventures, a global venture capital firm investing in gaming, consumer applications, and the technologies powering both.Phylicia joined Play Ventures as its first employee after nearly a decade working across marketing, growth, product, and startup operations. Today, she invests in game studios, technology companies, and a growing category that Play Ventures calls “playable apps”: consumer applications that incorporate the operating principles and engagement models perfected by the gaming industry.The central idea behind the conversation is simple: gaming is no longer becoming mainstream. It already is mainstream. Instead, everything else is becoming more like gaming.From Duolingo and Robinhood to Discord, fitness platforms, productivity tools, and short-form microdramas, consumer apps increasingly rely on mechanics developed or refined by game companies. Streaks, rewards, progression systems, virtual goods, social communities, live events, and freemium monetization have become foundational elements of the modern digital experience.The conversation also explores how Apple’s App Tracking Transparency framework forced mobile publishers to rethink their approach to growth. As deterministic user-level measurement became more difficult, leading publishers dramatically increased creative production and testing—sometimes producing thousands of advertising assets for a single title each month. Generative AI is now making that speed, volume, and personalization possible across a much broader range of industries.The discussion then turns to agentic advertising and what the emerging ecosystem may still be missing. While much of the industry is focused on buyer agents and seller agents, Phylicia argues that the greatest opportunity could be a third participant: an agent representing the consumer.A true consumer agent could understand an individual’s preferences, manage permissions, determine when advertising is welcome, filter irrelevant brands, transact on the consumer’s behalf, and protect that person’s interests across digital environments. In Phylicia’s view, the company that successfully builds a trusted and widely accessible consumer-agent layer could become one of the next trillion-dollar businesses.Along the way, they discuss:Why gaming remains misunderstood despite its enormous economic and cultural influencePhylicia’s path from growth marketing to becoming Play Ventures’ first employee and a General PartnerWhat separates a genuinely playable application from superficial gamificationHow progression, social interaction, virtual economies, and live operations drive retentionWhy microdramas are a powerful example of gaming principles entering entertainmentHow game companies measure cohorts, monetization, retention, and return on ad spendWhy leading publishers produce thousands of new advertising creatives every monthHow AI is reshaping creative production, localization, personalization, and live operationsWhat buyer, seller, and consumer agents could mean for the future of advertisingWhy women’s health remains one of the world’s largest underserved investment opportunitiesThis is a wide-ranging conversation about gaming, venture capital, consumer behavior, advertising, and AI. More than anything, it makes the case that if you want to understand where consumer technology is heading, you should pay much closer attention to what the gaming industry has already built.Learn more about Phylicia Koh:https://www.linkedin.com/in/phyliciakoh/Learn more about Play Ventures:https://www.play.vc/Visit Signal & Noise:https://www.signalandnoise.ai/

What if the best way to future-proof your career isn't learning another AI tool—but learning to think like a hacker?In this episode of Signal & Noise, Executive Voice Krish Raja sits down with Alanna Laforet—technology executive, former Chief Revenue Officer, startup operator, blockchain pioneer, and advisor—to explore what it really takes to reinvent yourself in an era where AI is transforming every industry.Alanna's career has never followed a traditional path. From starting as a Unix systems administrator and QA engineer at DoubleClick to helping shape advertising standards at the IAB Tech Lab, leading blockchain ventures, launching crypto media companies, advising AI startups, and building a portfolio career across multiple industries, she's consistently embraced curiosity over comfort.Together, Krish and Alanna unpack why the people who thrive in the AI era won't necessarily be those with the best technical skills—but those willing to continually learn, experiment, and reinvent themselves.They discuss:Why adopting a "hacker mentality" creates career resilienceHow curiosity—not job titles—has guided Alanna's professional journeyThe hidden lessons learned from startup failures, crypto winters, and industry disruptionWhy AI makes understanding technology more important, not lessHow to overcome fear and imposter syndrome when changing careersWhy treating yourself as your own company changes how you think about workThe rise of portfolio careers, fractional leadership, and multiple revenue streamsBuilding a personal thesis that guides career decisionsWhy networking, community, and simply "leaving your house" may be the most underrated career advice todayPractical advice for professionals navigating layoffs, AI disruption, and career transitionsThis isn't just a conversation about AI.It's a conversation about ownership, adaptability, and designing a career that's resilient no matter how technology changes.If you're wondering how to stay relevant in the age of AI—or considering your own next chapter—this episode offers a thoughtful roadmap from someone who's reinvented herself time and time again. Guest: Alanna LaforetTechnology Executive | Startup Advisor | Fractional Executive | Blockchain & AI StrategistHosted by: Krish RajaExecutive Voice, Signal & NoiseSubscribe to Signal & Noise for conversations with the executives, founders, researchers, and innovators shaping the future of AI, advertising, marketing, media, and technology.#AI #Careers #Leadership #FutureOfWork #CareerGrowth #ArtificialIntelligence #AdTech #MarTech #FractionalLeadership #Entrepreneurship #Blockchain #Innovation #SignalAndNoise #KrishRaja #AlannaLaforet

Artificial intelligence is transforming every industry—but what happens when it transforms an entire city?In this episode of Signal & Noise, hosts Rio Longacre and Brett House sit down with Suma Nallapati, Chief AI & Information Officer for the City and County of Denver, to explore one of the most important—and often overlooked—applications of AI: improving the lives of citizens.Rio and Suma first met during Mayor Mike Johnston's transition team, and this conversation brings together years of shared interest in technology, public service, and civic innovation. Rather than focusing on AI's impact on marketing or enterprise productivity, this discussion asks a bigger question:How can AI make society better?Suma shares how Denver has become one of America's leading AI-enabled cities, why she left the private sector to return to public service, and how city governments can embrace AI responsibly while maintaining public trust.From AI-powered citizen services and smart cities to responsible governance and the future of work, this is a thoughtful conversation about technology's role in creating stronger communities—not just more efficient businesses. Why Suma chose to leave executive leadership in the private sector to serve the people of DenverHow Denver became one of the first cities in the U.S. to appoint a Chief AI OfficerThe story behind Sunny, Denver's multilingual AI assistant that helps residents access city services 24/7How AI is improving government operations while keeping humans firmly in the loopWhy "transformational work should belong to humans, transactional work to bots"The importance of responsible AI, governance, and cross-functional oversightHow Denver balances innovation with public trust and citizen privacyWhat "smart cities" really mean—and why they're about people, not technologyLessons government leaders can learn from the private sector—and vice versaWhy AI adoption is becoming more about organizational change than technology itselfHow cities can prepare for an AI-native workforceThe evolving debate around AI regulation, data centers, and public policyWhy curiosity—not fear—is the most important leadership trait in the AI eraSuma's vision for how AI can help create a more compassionate and resilient society Whether you're a CIO, public sector leader, technologist, policymaker, entrepreneur, or simply curious about how AI will shape everyday life, this episode offers a refreshing perspective on technology's highest purpose: serving people.Guest: Suma NallapatiChief AI & Information OfficerCity and County of DenverIf you enjoyed this episode, be sure to subscribe to Signal & Noise on YouTube, Spotify, Apple Podcasts, or wherever you get your podcasts.#ArtificialIntelligence #AI #PublicSector #Government #SmartCities #DigitalTransformation #ResponsibleAI #Innovation #Leadership #CIO #ChiefAIOfficer #Denver #Technology #FutureOfWork #SignalAndNoise

Every AI breakthrough begins with something far less glamorous: clean, trustworthy data.In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Jer Tippets, Director of Digital Tagging & Implementation at Hyatt Hotels, to explore the invisible infrastructure that powers modern digital marketing. While everyone is talking about generative AI, personalization, and autonomous agents, Jer argues that none of it works without a solid data foundation—and after spending more than 15 years building customer data systems for global brands, he's uniquely qualified to explain why. Rio first met Jer when they were both speakers at Tealium's Digital Velocity Conference, where Hyatt shared its customer data strategy and philosophy of treating customers like humans. Hyatt has long been a Tealium customer, and Tealium—one of Signal & Noise's valued sponsors—has played an important role in helping leading enterprises modernize their customer data infrastructure. That shared connection made this conversation a natural fit and one we've wanted to have ever since.Together, they dive into why poor data quality quietly kills AI initiatives, why organizations continue to collect mountains of unusable information, and why "collect everything" has become one of the biggest mistakes in modern marketing. Jer explains why first-party data is now one of the most valuable strategic assets a company can own—and why governance, identity resolution, and privacy have become board-level business issues rather than back-office technical concerns. The conversation also pulls back the curtain on Hyatt's approach to digital experience, exploring how one of the world's largest hospitality brands balances personalization with consumer trust across millions of guest interactions. From persistent customer identities and consent management to CDPs, synthetic audiences, and the promise—and reality—of AI-driven personalization, Jer offers a refreshingly practical perspective shaped by years of real-world implementation. Rather than chasing hype, he focuses on what actually delivers better customer experiences. Jer also shares why AI should be viewed as an amplifier—not a replacement—for human expertise, why data governance is becoming one of the most important competitive advantages organizations can build, and what the next generation of digital measurement will look like as AI agents increasingly become both the producers and consumers of marketing data.If you've ever wondered why some brands consistently deliver seamless, personalized experiences while others struggle with fragmented customer journeys, this episode explains what happens behind the scenes—and why the future of AI may ultimately depend less on better models and more on better data.Why AI is only as good as the data beneath itHow Hyatt approaches customer identity and digital experienceWhy first-party data has become a strategic business assetThe hidden costs of poor data qualityPrivacy, consent management, and earning customer trustWhy "collect everything" is the wrong data strategyThe realities of CDPs, synthetic audiences, and identity resolutionHow AI is changing digital implementation and analyticsWhy governance is becoming a competitive advantageWhat marketers should do today to prepare for an AI-first futureWhether you're a CMO, MarTech leader, data engineer, product owner, analytics professional, or simply fascinated by the future of AI and customer experience, this conversation offers an inside look at the systems powering every click, every recommendation, and every personalized interaction.Guest:Jer TippetsDirector of Digital Tagging & ImplementationHyatt Hotels

For nearly two decades, digital advertising has optimized around one primary objective: finding the cheapest possible way to reach the right person. Programmatic buying, identity signals, attribution, and performance marketing have created extraordinary efficiency—but they may also have trained the industry to systematically undervalue one of the most important variables in advertising effectiveness: the quality of the media itself.In this episode of Signal & Noise, Rio Longacre and Brett House welcome back friend of the podcast Erez Levin for his third appearance and his second full-length conversation. Erez is one of the industry's most respected voices on media quality, attention, and advertising effectiveness. A former Google executive and now Founder of Emet Advisory Advisory, he recently co-authored CIMM's landmark report, Quality Matters: Navigating Quality in Media Buying and Measurement, an effort to establish a common industry framework for evaluating media quality.The conversation explores a simple but powerful premise:Not all impressions are created equal.While the industry has become exceptionally good at optimizing for identity, CPMs, and short-term outcomes, it has largely ignored the environments where advertising actually appears. As deterministic identity signals become less reliable and privacy regulations reshape digital advertising, Erez argues that marketers must begin treating media quality as a first-class buying signal—not merely a brand safety filter.Topics include:Why optimizing exclusively for ROAS and CPMs can quietly destroy long-term brand growthHow the industry's obsession with attribution created a "race to the bottom" in media buyingWhy attention alone is an incomplete measurement frameworkThe difference between audience quality, media quality, and creative quality—and why all three matterWhy premium inventory isn't binary, but exists on a spectrum of valueThe hidden problems with averaging performance across wildly different media environmentsWhy CTV has an opportunity to avoid repeating the mistakes of display advertisingHow marketers should rethink media planning as identity signals continue to weakenWhy procurement incentives often work against advertising effectivenessPractical ways brands can begin incorporating media quality into buying decisions todayThe future of AI-driven media buying and whether automation will improve—or worsen—advertising qualityWhy marketers—not platforms or agencies—must ultimately lead this shiftThe discussion also expands into broader industry questions, including the future of the open web, the role of private marketplaces, the economics of connected television, media governance, AI-generated advertising, and whether today's measurement systems are rewarding the wrong behaviors.Throughout the conversation, Erez makes the case that quality is not a "nice to have." It is a pricing signal. One that may become increasingly important as AI, automation, and privacy reshape the advertising ecosystem.If you've ever wondered why digital advertising often feels more optimized than effective—or why brands continue chasing cheaper impressions while premium publishers struggle to monetize quality—this conversation explains why.Whether you're a CMO, agency executive, media planner, AdTech leader, publisher, or simply interested in where digital advertising is headed next, this is an essential discussion about one of the industry's most important strategic shifts.Guest: Erez Levin, Founder, Emmett Advisory; former Google executive; co-author of CIMM's Quality Matters report.Connect with Erez: https://www.linkedin.com/in/erezlevin/

This week, the future of digital advertising arrived.Following Boostr and Vox Media’s landmark announcement of one of the industry’s first public agentic media buys using AdCP, Signal & Noise sits down for an exclusive conversation with Patrick O’Leary, Founder & CEO of Boostr, to unpack exactly what happened—and why it matters.For months, we’ve argued that agentic trading wasn’t a distant vision. It was already beginning. This announcement is one of the clearest signals yet that AI agents are moving beyond copilots and into autonomous negotiation, with buyer and seller agents working directly together to execute media transactions.This isn’t another AI hype discussion.Patrick walks us through the transaction in detail: how the agents negotiated, what humans still controlled, how long the process took, what the pilot revealed, and why this could fundamentally reshape the economics of digital advertising.We also tackle the bigger questions:Does agentic trading replace programmatic or evolve alongside it?What happens to DSPs, SSPs, and today’s ad tech ecosystem?How do identity, fraud prevention, brand safety, and measurement work in an agent-driven world?Which companies stand to benefit—and which business models are suddenly at risk?At Signal & Noise, we don’t do hot takes. We bring together the people who are actually building the future and give them the time to explain what they’re doing, why they’re doing it, and what it means for the rest of the industry.If you’ve been wondering whether agentic trading is real, this is the conversation you’ve been waiting for.Guest: Patrick O’Leary, Founder & CEO, BoostrIf you enjoy conversations that go beyond the headlines, subscribe to Signal & Noise on YouTube, Spotify, Apple Podcasts, or visit SignalAndNoise.ai for more executive interviews, analysis, and original research.

Attribution was supposed to get easier. Instead, marketers today operate in a world of disappearing identifiers, privacy restrictions, walled gardens that increasingly measure themselves, and consumer journeys that unfold inside environments few advertisers can fully observe.So how much confidence should we still have in the numbers? In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Brian Quinn, President & GM of AppsFlyer, one of the most influential—but often least understood—companies in digital advertising.For more than a decade, AppsFlyer has been at the center of mobile measurement, helping brands understand where users come from, which campaigns actually drive installs and engagement, and how to measure effectiveness in an ecosystem transformed by Apple’s ATT framework, signal loss, and evolving privacy regulations.Together, we unpack one of the industry’s most important questions: Can attribution still be trusted?The conversation explores why mobile remains the dominant yet underappreciated consumer environment, whether multi-touch attribution still has a future, and why marketers are increasingly turning toward incrementality, clean rooms, and econometric approaches to understand what really drives business outcomes.We also discuss:• Why AppsFlyer became much more than an attribution company• Whether the walled gardens are effectively grading their own homework• The lasting impact of Apple’s App Tracking Transparency changes• Why fraud remains a massive hidden tax on digital advertising• The growing role of clean rooms and independent measurement• Whether privacy has made advertising measurement better—or simply more uncertain• How AI may reshape attribution and optimization over the next five years• What a modern measurement strategy should look like in a world where signal loss may be permanentApps account for nearly 90% of mobile time, consumers spend hours each day inside apps, and marketers collectively spend more than $150 billion annually on mobile advertising. Yet many advertisers still struggle to explain how mobile attribution actually works—or what replaces it when deterministic signals disappear.Brian offers a candid and practical perspective on where measurement is heading next, what marketers misunderstand about attribution, and what parts of today’s measurement stack may disappear entirely.If you’ve ever wondered whether the industry’s most trusted metrics deserve your trust—or what comes after attribution—this episode is for you.#SignalAndNoise #AppsFlyer #Attribution #Measurement #Privacy #AdTech #MarTech #MobileMarketing #CleanRooms #MTA #Incrementality #DigitalAdvertising

Colorado has become ground zero in one of the most important debates shaping the future of technology: how do we regulate AI without slowing innovation?In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Srinivas "Chinnu" Parinandi, Associate Professor of Political Science at the University of Colorado Boulder, to unpack the growing clash between government oversight, technological progress, and economic competitiveness.The conversation begins with Colorado's controversial AI legislation and expands into a broader discussion about privacy regulation, federalism, interstate commerce, and the unintended consequences of state-by-state technology governance. Chinnu explains why populism on both the political left and right is driving increased scrutiny of technology companies, how fragmented regulation affects startups versus large incumbents, and why policymakers often struggle to keep pace with rapidly evolving technologies. The discussion also explores the influence of GDPR and other privacy frameworks, whether regulatory uncertainty is becoming a barrier to entrepreneurship, and how businesses can engage more constructively with policymakers rather than simply opposing regulation. Chinnu offers a nuanced perspective on whether America needs a national AI framework and why the answer may be more complicated than many in the tech industry assume. In the second half of the episode, the conversation turns to one of the most overlooked aspects of the AI boom: data centers. As AI workloads drive unprecedented demand for computing power, local opposition to data center projects is growing across the country. Chinnu explains the politics behind energy consumption, power generation, utility regulation, zoning battles, and the increasing tension between infrastructure development and community concerns. The episode closes with a discussion of whether America is entering an "anti-tech era," what role government should play in shaping emerging technologies, and whether the United States can strike the right balance between consumer protection and innovation in the age of AI. Colorado's AI laws and privacy regulationsSB26-134 and SB26-189GDPR, CCPA, and state-level privacy frameworksAI regulation and interstate commerceFederal vs. state governancePopulism and technology policyStartup innovation and regulatory burdenData centers, energy, and infrastructureNIMBYism and local opposition movementsAmerica's AI competitiveness versus ChinaThe future of AI governanceSrinivas Parinandi is an Associate Professor of Political Science at the University of Colorado Boulder whose research focuses on political economy, American political institutions, public policy, technology governance, and the interaction between government regulation and business innovation. His work examines how political incentives and institutional structures shape economic outcomes and emerging technology markets.#AI #ArtificialIntelligence #Privacy #GDPR #CCPA #Colorado #DataCenters #TechnologyPolicy #Regulation #PoliticalEconomy #SignalAndNoise #AdTech #Innovation #TechPolicy #AIRegulation

What happens when you stop trying to sound "professional" and start sounding like yourself?In this Signal & Noise conversation, Executive Voice Krish Raja hosts his first solo episode with Justin Kramm, Founder & Creative Director of Shit Show Creative. The result is one of our funniest—and most surprisingly insightful—conversations to date.Justin has spent more than two decades shaping creative work for brands including Nike, Red Bull, NVIDIA, Xbox, Uber, ESPN, and many others. More recently, he's built an enormous following on LinkedIn by doing something refreshingly different: embracing absurdity, authenticity, and humor to build a genuine community.Together, Krish and Justin explore:Why authenticity attracts the right people—and the right opportunitiesHow humor cuts through noise, tribalism, and corporate clichésBuilding a creative business that started as a joke and became something realWhat Cannes Lions reveals about creators, AI, and the future of marketingWhy LinkedIn may be becoming the internet's most unexpectedly entertaining platformHow AI should amplify creativity rather than replace itWhy finding your authentic voice is ultimately how you find your tribeRecorded while Krish was attending Cannes Lions and Justin joined remotely from Florida in the middle of the night, this episode blends sharp observations about the advertising industry with an honest conversation about creativity, community, and having the courage to be yourself.It's funny. It's thoughtful. And it's a reminder that sometimes the best professional strategy is simply being authentically human.

Day 4 marks the final chapter of Signal & Noise’s first Cannes Lions together as a team—and what a way to close out an unforgettable week.Across four days at Hearst House, we recorded conversations with some of the brightest minds in advertising, media, identity, AI, cybersecurity, consulting, and marketing transformation. Cannes 2026 felt bigger, busier, and more energized than ever, with AI moving from theory to implementation and nearly every discussion centered on what happens when intelligent systems begin participating directly in media, commerce, and customer experiences.In this Day 4 compilation, Rio Longacre, Brett House, and Krish Raja sit down with an exceptional group of founders, CEOs, technologists, and industry operators to unpack the trends shaping the next decade of marketing.Featured guests include:• Michael Beebe, CEO of Dstillery, joined by David Bell, for a candid discussion on transparency, principal media, agency business models, ad tech taxes, and whether AI will finally expose which vendors are truly creating value.• Guy Tytunovich, Founder & CEO of CHEQ, on fighting ad fraud in an era of AI agents, malicious bots, and non-human traffic—and why marketers may need entirely new approaches to identity and trust online.• Mansoor Basha, CTO of Stagwell Marketing Cloud, on composable marketing systems, data infrastructure, and the evolving role of AI inside enterprise decision-making.• Alina Vandenberghe, Co-Founder & Co-CEO of Chili Piper, discussing growth, customer experience, and how AI is reshaping B2B engagement.• Justin Bell, Global CEO of Credera, sharing his perspective on transformation, enterprise AI adoption, and why consulting firms are increasingly helping clients rethink operating models—not just technology stacks.• Rob McLaughlin returns to Signal & Noise for a wide-ranging conversation touching on curation, supply-side innovation, containerization, publisher monetization, and why Cannes remains the industry’s most valuable gathering.And to close out the week, Lou Paskalis delivers one of our favorite observations from Cannes:“The only thing worse than having to come to Cannes is not getting to go to Cannes.”From fraud detection and AI agents to transparency, identity, curation, and the future of marketing as an enterprise operating system, Day 4 captures the optimism, curiosity, and collaborative spirit that made Cannes Lions 2026 one of the most exciting events we’ve attended.Thank you to everyone who joined us at Hearst House, stopped by the studio, shared ideas, challenged assumptions, and helped make this such a memorable week.This is the final Cannes Lions 2026 compilation episode from Signal & Noise—but the conversations are only getting started.🎧 Available now on Apple Podcasts and Spotify.📺 Individual interviews from Cannes Lions 2026 will continue to roll out on YouTube in the coming weeks.#CannesLions #AI #AdTech #MarTech #Identity #Cybersecurity #AgenticAI #SignalAndNoise #HearstHouse #Advertising #MarketingInnovation

Day 3 at Cannes Lions 2026 may have been the hottest day in French history, but it also delivered some of the most thoughtful conversations of the week.Recorded live from Hearst House in Cannes, this Signal & Noise compilation brings together founders, CMOs, product leaders, publishers, identity experts, and healthcare innovators to discuss what’s actually changing in advertising, media, data, and AI.A recurring theme throughout the day was that we’re entering a new phase of the AI era. The prototypes are everywhere, but deployment is hard. Brands are still wrestling with fragmented data, trust, context, measurement, and figuring out how agentic systems fit into real business workflows. At the same time, publishers are rediscovering the value of premium relationships, healthcare marketers are embracing AI-driven disruption, and identity is becoming strategically important again.🎙 Sarah Robertson – Chief Product Officer, ExperianTrusted data, identity as infrastructure, MCPs, consumer agents, and why product teams are being pushed to build capabilities the market isn’t quite ready to consume.🎙 Christian Monberg – CTO, Zeta GlobalAthena, agentic marketing, the new partnership with Palantir, and why brands still haven’t solved their data foundations despite years of investment in martech stacks.🎙 David Sandström – CMO, KlarnaHow Klarna transformed itself from a B2B payments provider into a consumer brand, designing financial experiences for real people instead of “tech bros,” and why shopping remains an emotional experience that agents won’t fully replace.🎙 Jim Weiss – Founder & Chairman, Real ChemistryThe future of healthcare marketing, precision medicine, longevity, physician influence, and why healthcare may be the industry most ripe for AI disruption.🎙 Matt Krepsik – CEO, MediaRadarMMM, metadata, trust, context, speed, creative effectiveness, and how AI may finally make marketing measurement actionable in near real time.🎙 Mathieu Roche – Founder & CEO, ID5Identity as advertising infrastructure, the implications of the Publicis acquisition of LiveRamp, and what happens when consumer agents begin acting as extensions of ourselves online.🎙 Melissa Gordon-Ring – Global President, Omnicom Media Group HealthHealthcare’s emergence at Cannes, AI’s impact on clinical development and commercialization, and why pharma marketers may ultimately benefit most from agentic technologies.🎙 Lisa Ryan Howard – Global CRO, Hearst MagazinesPublishers are back. Hearst discusses premium audiences, first-party data products, AI-powered sales tools, direct relationships, and why quality content is becoming more valuable in an era of infinite AI-generated noise.This was our third day together at Cannes Lions 2026, and the themes were impossible to ignore:• AI is exposing weaknesses in existing technology stacks.• Trusted data matters more than ever.• Identity isn’t dead—it’s evolving.• Publishers may finally have leverage again.• Healthcare is becoming one of the most exciting categories in marketing.• Creativity still outperforms algorithms when it comes to moving people.More Cannes conversations are coming soon, including our Day 4 recap and additional individual interviews from Hearst House.Subscribe to Signal & Noise on Apple Podcasts and Spotify, and watch individual sessions as they are released here on YouTube.

With Rio Longacre, Krish Raja & Brett HouseSignal & Noise is on the ground at Cannes-Lions 2026.This year marks the first time Rio Longacre, Krish Raja, and Brett House have attended Cannes together as a team under the Signal & Noise banner. While each of us has been to Cannes in previous years, experiencing it together—and recording conversations live from Hearst House—made this year’s festival something special.And what a year to do it.Cannes Lions 2026 felt bigger, busier, and more energized than ever. The familiar faces from advertising, media, and publishing were all here, but what stood out most was the influx of AI founders, product leaders, engineers, and technologists who are increasingly shaping the future of our industry.This special compilation brings together our Day 1 opening conversation along with every interview recorded during Days 1 and 2 at Hearst House.Across these sessions, we explored some of the biggest themes emerging from Cannes:• Agentic media buying and autonomous analytics• The transformation of agencies into AI-native operating models• Self-service television and the future of premium video advertising• AI-powered measurement, causal modeling, and MMM• The reinvention of creative workflows• Healthcare marketing, discoverability, and the changing physician experience• The role of creators, influencers, and culture in modern brand building🎙 John Hoctor — CEO & Co-Founder, Newton Research; Founder of Data Plus MathJohn discusses analytics agents, causal modeling, MMM, and how Newton is helping agencies such as Horizon Media and Dentsu build toward an agentic future for planning, measurement, and buying.🎙 Robyn Freye — President, Court AvenueRobyn shares her perspective on enterprise AI transformation, organizational redesign, and what it means to build an AI-native agency designed for the intelligence economy.🎙 Daniel Druger — VP Product, Comcast Advertising / Universal AdsDaniel walks through Universal Ads, Comcast’s effort to bring self-service buying to premium television, making TV advertising accessible to millions of businesses that historically couldn’t participate.🎙 Brian Vaughan — Executive Creative Director, ShadowBrian explores how creativity is evolving in the age of AI, why culture-first campaigns still matter, and how PR, creators, celebrity partnerships, and social storytelling can work together to create moments that break through the noise.🎙 Andrea Palmer — CEO, PHM (Publicis Health Media)Andrea discusses healthcare marketing’s evolution from compliance-driven communications to discoverability, influence, and helping physicians and patients navigate an increasingly complex information ecosystem.This compilation episode is available in full on Apple Podcasts and Spotify, while each individual conversation will also be released separately here on YouTube.And we’re only halfway through the week.Days 3 and 4 are coming soon, featuring even more founders, product leaders, agency executives, publishers, and technologists helping define what comes next for media, marketing, AI, and advertising.Stay tuned.🎧 Full compilation available on Apple Podcasts and Spotify📺 Individual interviews dropping soon on YouTubeFeatured Guests📰 More Cannes coverage, articles, and episodes at SignalAndNoise.ai

For weeks, reports that Publicis was exploring a relationship with Hightouch following its acquisition of LiveRamp circulated as an industry scoop. Until now, no one involved had publicly confirmed it.In this special Signal & Noise Signal Break, we sit down with Hightouch co-founder and CEO Tejas Manohar, who confirms that Hightouch has in fact been in discussions with Publicis.That confirmation adds an important new dimension to one of the biggest stories in adtech this year. What would a partnership between Publicis, LiveRamp, and Hightouch mean for identity, activation, clean rooms, and the future architecture of customer data?Rio Longacre, Brett House, and Tejas unpack the implications in a fast-moving, high-energy conversation between three practitioners deeply involved in modern marketing infrastructure. We discuss composable CDPs, warehouse-native activation, agentic workflows, and why the industry's center of gravity may be shifting yet again.To be clear, Hightouch is a sponsor of Signal & Noise, but sponsorship played no role in our interest in covering this story or inviting Tejas to join us. This discussion was driven entirely by the significance of the news and our belief that it deserves broader industry attention.This isn't the long-form Tejas episode we originally planned. That's still coming. Consider this an early dispatch—a Signal Break—to share an important confirmation with the market while it's still unfolding.Topics discussed:• Tejas confirms Hightouch has spoken with Publicis• What a Publicis–LiveRamp–Hightouch relationship could look like• Why composable architectures continue gaining momentum• How identity, activation, and measurement may evolve post-acquisition• The growing role of AI and agentic systems in marketing operationsIf you're trying to understand where the future marketing operating system is headed, this is one conversation you won't want to miss.

Signal & Noise ExclusivePublishers create the content. Publishers build the audiences. Publishers bear the costs.Yet somehow, after two decades of digital advertising innovation, many publishers capture only a fraction of the value they create.In this Signal & Noise exclusive, Rio Longacre and Brett House sit down with Keith Petri, SVP of Data, Identity & Supply at Viant, and Rich Hyden, SVP of Publisher Solutions at Viant, for a deep discussion on one of the most important questions facing the open internet:Can publishers reclaim their economic future—or are the economics of digital media fundamentally broken?This conversation coincides with Viant's major announcement of Viant Publisher Solutions, a new suite of capabilities designed to improve transparency, signal quality, monetization, identity activation, and supply-path efficiency for publishers while simultaneously improving advertiser outcomes. It represents one of the most significant publisher-focused initiatives launched by a major DSP in recent years.But this episode goes far beyond a product launch.Together, Keith and Rich unpack the realities of modern publisher monetization, the hidden inefficiencies inside today's programmatic supply chain, why signal quality increasingly determines revenue, and how identity has become one of the most valuable assets publishers possess.The discussion explores how technologies such as SupplyIQ, Direct Access, Household ID, and IRIS_ID aim to create a more direct relationship between buyers and sellers while reducing friction, duplication, and information loss throughout the advertising ecosystem.Along the way, the conversation tackles some of the biggest debates in advertising today:Why premium publishers continue to struggle despite creating enormous valueWhether supply-path optimization helps publishers—or hurts themThe role of identity in driving publisher revenueWhy signal quality may be the new currency of digital advertisingHow CTV is reshaping publisher economicsThe growing power of walled gardens versus the open internetWhy contextual intelligence is becoming increasingly importantHow AI and agentic media buying may transform programmatic advertisingWhether DSPs can play a meaningful role in helping publishers thriveWhat the future of publisher monetization looks like over the next decadeKeith and Rich also share a fascinating perspective from inside one of the industry's most innovative DSPs, explaining why better advertiser outcomes and healthier publisher economics may no longer be competing objectives.For anyone working in digital media, ad tech, publishing, identity, programmatic advertising, retail media, CTV, measurement, or AI-powered marketing, this is a conversation packed with practical insights and big-picture thinking.The future of the open internet may depend on whether buyers and sellers can become more aligned.This episode explores what that future could look like.GuestsKeith Petri, SVP Data, Identity & Supply, ViantRich Hyden, SVP Publisher Solutions, ViantHosted ByRio LongacreBrett HouseTopics CoveredPublisher Monetization • Programmatic Advertising • Supply Path Optimization (SPO) • CTV • Identity Resolution • First-Party Data • Household ID • Contextual Targeting • Publisher Data Strategy • AI Advertising • Agentic Media Buying • Open Internet Economics • Ad Tech Infrastructure • Signal Quality • Media Quality • Digital Advertising#SignalAndNoise #AdTech #ProgrammaticAdvertising #Viant #PublisherMonetization #CTV #IdentityResolution #DigitalAdvertising #RetailMedia #AIAdvertising #OpenInternet #MarketingTechnologyEnjoy!

What happens when an early Amazon engineer who helped pioneer automated advertising leaves AdTech behind to build the world's fastest commercial airliner?In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Blake Scholl, Founder and CEO of Boom Supersonic, for a wide-ranging conversation about innovation, entrepreneurship, aviation, AI, and why some of the world's biggest opportunities are hiding in plain sight.Before launching Boom, Blake helped shape early internet advertising at Amazon, worked through the hypergrowth years at Groupon, and experienced firsthand the rise of AdTech, recommendation engines, and large-scale customer acquisition systems. Then he made an unlikely leap: leaving software behind to tackle one of the hardest problems in engineering—bringing commercial supersonic flight back from the dead. The discussion explores what Blake learned from Amazon, why he believes Groupon missed a once-in-a-generation opportunity, and how short-term thinking can destroy even the most promising companies. Along the way, he shares stories about crashing Google AdWords, building the world's largest spam operation at Groupon, and getting some of his toughest lessons directly from Jeff Bezos. The conversation then shifts to Boom Supersonic's mission, the history of the Concorde, the regulatory decisions that stalled aviation innovation for decades, and Blake's controversial view that technological progress didn't slow because the problems became harder—it slowed because society stopped pursuing them. Blake also reveals the behind-the-scenes story of Boom's near-collapse, the seven-year pursuit of a partnership with Rolls-Royce, and how a failed engine deal ultimately led to one of the company's biggest breakthroughs: building its own propulsion technology and creating a new turbine business that may help fund the future of supersonic travel. The episode closes with Blake's thoughts on AI, entrepreneurship, and why the biggest impact of AI may not be job replacement—but the creation of millions of new builders capable of turning ideas into reality. Blake Scholl's journey from Amazon and Groupon to Boom SupersonicEarly AdTech, automated advertising, and internet growth storiesLessons from Jeff Bezos and Amazon's long-term thinking cultureGroupon's rise, fall, and missed platform opportunityWhy innovation in aviation stalled after ConcordeRegulatory capture and the history of supersonic flightBuilding Boom Supersonic from scratchThe failed Rolls-Royce partnership and Boom's engine strategyTurbine power generation, AI infrastructure, and data centersThe future of commercial supersonic travelWhy AI may create more entrepreneurs than ever beforeLong-term thinking, risk-taking, and building hard-tech companiesWhether you're interested in aviation, startups, AI, AdTech, or the future of innovation itself, this is a fascinating conversation about what happens when someone decides to stop optimizing digital systems and start building physical ones.#SignalAndNoise #BoomSupersonic #BlakeScholl #Aviation #SupersonicFlight #AI #Entrepreneurship #Innovation #Amazon #Groupon #AdTech #MarTech #HardTech #Technology #FutureOfWork #CommercialAviation #ArtificialIntelligence #StartupLeadership #Engineering #DigitalTransformation

What happens when the technology that powers advertising becomes the thing consumers interact with directly? In this episode of Signal & Noise, Rio Longacre and Brett House sit down with industry analyst Karsten Weide to explore one of the most important—and controversial—questions facing the digital economy: how AI will ultimately make money.From advertising inside chatbots to agentic commerce, autonomous media buying, and the future of the open web, Karsten shares why he believes AI will reshape advertising more profoundly than any technology shift he has witnessed in more than three decades covering media, technology, and digital advertising. The conversation examines the rapid emergence of agentic AI across the advertising ecosystem, the growing role of automation in media planning and optimization, and why the traditional programmatic supply chain may be heading toward a fundamental transformation. Karsten explains how platforms, DSPs, SSPs, publishers, agencies, and brands are all racing to build their own agentic operating systems—and what that means for the future structure of the advertising market. The discussion also tackles one of the industry's most debated topics: advertising inside AI products. Will OpenAI, Google, Anthropic, and Perplexity eventually embrace advertising as a major revenue stream? What will AI-native ad formats actually look like? And can advertising coexist with the trust users expect from conversational interfaces? The conversation then turns to agentic commerce—the emerging world where AI agents shop, compare products, negotiate prices, and make purchases on behalf of consumers. If agents become the primary buyers, what happens to search advertising, performance marketing, and the broader digital advertising ecosystem? Karsten offers a provocative perspective on why this future may create a surprising renaissance for brand advertising, display, video, audio, and out-of-home media. Along the way, the group discusses:Why AI adoption in advertising is still in its earliest stagesThe rise of autonomous media buying and agentic workflowsHow Amazon, Google, Meta, and emerging ad tech players are approaching AI-powered advertisingThe future of SMB advertising and self-service media buyingThe battle between open standards and proprietary AI ecosystemsWhy the programmatic supply chain may look dramatically different in five yearsThe opportunities and risks of AI-driven creative productionWhether AGI is actually closer than most people thinkHow AI could reshape agency operating models and industry employmentIf you've been wondering how advertising, commerce, media buying, and consumer behavior evolve in a world increasingly shaped by AI agents, this episode provides one of the most thoughtful and grounded discussions available today.The future of advertising may not be humans buying from brands. It may be agents buying from agents. And the implications are enormous.

What happens when a society can no longer agree on basic facts?In this episode of Signal & Noise, Rio Longacre and Brett House sit down with Vanessa Otero, Founder and CEO of Ad Fontes Media and creator of the influential Media Bias Chart, to explore the growing crisis of trust, polarization, and information quality in the modern media landscape.Vanessa's Media Bias Chart began as a personal project during the 2016 election cycle and has since evolved into one of the most widely recognized frameworks for evaluating media bias and reliability. Today, Ad Fontes Media has analyzed tens of thousands of articles, podcasts, and news sources to help consumers, educators, advertisers, and publishers better understand the fragmented information ecosystem. The conversation explores how the industry arrived at a moment where millions of people consume different versions of reality, why social media algorithms amplify outrage and identity over truth, and whether objective journalism is still possible in an era dominated by platforms, creators, and AI-generated content. Vanessa shares her perspective on the collapse of trust in institutions, the economics of journalism, and why the survival of high-quality reporting matters far beyond the news business itself. The discussion also dives into the business challenges facing journalism. As local newspapers disappear, digital advertising consolidates around a handful of technology platforms, and AI reshapes content discovery, many news orgs are struggling to sustain the costly work of original reporting. Vanessa explains why journalism functions as critical societal infrastructure, how advertising incentives have unintentionally weakened the news ecosystem, and why she believes advertisers have a role to play in preserving high-quality information. Rio and Brett challenge Vanessa on whether audiences actually want objective reporting, the role of algorithms in reinforcing worldviews, and whether we're witnessing a return to a more fragmented media environment reminiscent of the pre-broadcast era. Together they explore the tension between engagement and truth, the rise of podcasts and creator-driven media, and whether consumers are becoming more aware of the ways technology influences their perception of reality. The episode also examines the future of advertising against news content. Vanessa discusses Ad Fontes Media's work helping advertisers identify high-quality news environments, the importance of context and trust in media buying, and why she believes many brands have made a mistake by avoiding news altogether. The conversation touches on CTV, media quality signals, brand safety, and the emerging role of AI in both improving and undermining the information ecosystem. Whether you're a marketer, publisher, journalist, technologist, policymaker, or simply someone trying to make sense of today's media environment, this conversation offers a thoughtful and nuanced look at one of the most important challenges facing modern society.The origin story of the Media Bias ChartWhy people increasingly live in separate realitiesTrust, misinformation, and disinformationThe collapse of local journalismSocial media, algorithms, and outrage economicsWhy advertisers stopped buying newsThe business model crisis facing publishersAI-generated content and the future of journalismPodcasts, creators, and media fragmentationNews quality, media trust, and brand safetyCTV advertising and Ad Fontes Media's partnership with ViantWhether objective journalism is still possibleVanessa Otero is the Founder and CEO of Ad Fontes Media, the company behind the Media Bias Chart. A former patent attorney, Vanessa launched the chart during the 2016 election cycle to help people better understand media bias and reliability. Today, Ad Fontes Media provides media quality ratings used by advertisers, publishers, educators, researchers, and consumers seeking greater transparency in the information ecosystem.

What happens when AI stops assisting media teams and starts acting on their behalf?In this episode of Signal & Noise, we sit down with Ethan Settel, Head of Sales & Accounts at Newton Research, to explore one of the most important developments in advertising today: the emergence of agentic media buying.While much of the industry remains focused on AI tools that summarize dashboards, generate briefs, or automate reporting, Newton Research is pursuing something far more ambitious. The company is building specialized AI agents that can connect data, execute advanced analytics, build forecasting models, recommend optimizations, and increasingly interact directly with media platforms to support planning, buying, and activation. At the center of our conversation is a provocative thesis: the future of advertising may be negotiated by machines.Rather than relying on human teams to manually interpret reports, adjust budgets, and coordinate across dozens of disconnected systems, agentic platforms like Newton are creating teams of AI specialists that can work together to analyze campaign performance, simulate scenarios, and execute media decisions with unprecedented speed and precision. These agents can communicate with DSPs, publishers, clean rooms, and planning tools, transforming what has historically been a fragmented and labor-intensive process into an increasingly automated operating model. We also discuss Newton’s groundbreaking work with NBCUniversal, FreeWheel, Yahoo, and Locality, where buy-side and sell-side AI agents collaborated to support premium video buying across linear television and streaming. The initiative offers a compelling glimpse into a future where software agents negotiate inventory directly with one another, potentially reshaping the role of DSPs, SSPs, and other intermediaries throughout the advertising ecosystem. Along the way, Ethan explains why measurement and analytics are the foundation of any effective agentic system. Without trusted data, consistent models, and full transparency into how decisions are made, automation simply amplifies errors. Newton addresses this by combining its proprietary marketing science knowledge base with each client’s unique methodologies, creating a repeatable and highly customized intelligence layer that becomes more valuable over time. We also explore some of the biggest questions facing the industry:How AI agents differ from generic tools like OpenAI ChatGPT, Anthropic Claude, and Google GeminiWhy data normalization has historically consumed most of a data scientist’s timeHow agentic systems can democratize advanced analytics for planners and buyersThe role of protocols such as MCP and AdCP in enabling agent-to-agent communicationWhether DSPs and SSPs become strategic platforms or simply “dumb pipes”Where liability and accountability sit when AI begins making media decisionsWhy human oversight remains essential, even as automation acceleratesEthan also shares his perspective on the organizational impact of agentic AI. Rather than replacing media professionals outright, he argues that the technology frees analysts, planners, and buyers from repetitive manual work, allowing them to focus on strategy, experimentation, and innovation. The result is not fewer insights, but potentially unlimited analytics applied to every campaign and every decision. This conversation offers a rare and highly practical look at what applied AI actually looks like inside advertising. It moves beyond hype to examine how real systems are being deployed today to transform measurement, planning, and activation.If Ethan is right, the future of media will not be defined by faster reporting or prettier dashboards. It will be defined by intelligent agents negotiating with one another across the buy-side and sell-side, continuously optimizing outcomes in a market that becomes more automated, transparent, and data-driven than ever before.The negotiated future has already begun.

The MarTech landscape exploded from a few hundred tools to more than 15,000. But according to Scott Brinker, the real story isn’t software sprawl — it’s the collapse of the silos between marketing, advertising, data, AI, and enterprise operations....In this episode, we sit down with the “Godfather of MarTech” to unpack one of the biggest shifts happening in modern business: the convergence of MarTech and AdTech into a new AI-driven operating model for marketing.We explore why the old world of disconnected systems, fragmented customer journeys, and rigid SaaS categories is breaking apart — and what replaces it. From first-party data and composable architecture to agentic AI and context engineering, Scott lays out a vision for a future where marketing systems become less about interfaces and workflows… and more about intelligence, orchestration, and decision-making.We also dig into:Why the SaaS business model is under pressureThe rise of the “hyper-tail” of custom AI-built softwareWhy analytics may be the first MarTech category fully disrupted by AIThe hidden organizational problem behind poor data strategyWhy “context” may become the most important concept in enterprise softwareHow AI is changing the relationship between platforms, APIs, services, and custom developmentWhy brands need to rethink the divide between owned media and paid mediaThe future of composable MarTech stacks and semantic data layersWhy the next generation of marketers will need radically different skillsScott also shares his perspective on:The evolution from suites → ecosystems → composable AI systemsWhy traditional UI-driven software may be headed toward a major transformationThe role of first-party data in connecting customer experience across channelsWhy most organizations still aren’t prepared for the operational realities of AIAnd why the companies that bridge MarTech and AdTech most effectively may have a major competitive advantage in the years aheadThis conversation goes deep into the infrastructure layer of modern marketing — but ultimately it’s about something bigger: how organizations make decisions in an AI-native world.If you care about:AI + marketingComposable architectureCustomer data strategyEnterprise softwareAgentic workflowsThe future of SaaSOr the convergence of MarTech, AdTech, and DataTech……this is a must-listen episode.

What if nearly half of every dollar spent on Connected TV is being wasted before an ad is ever served to the right person?In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Scott McKinley, one of the advertising industry’s most outspoken voices on data quality and identity. As founder and CEO of Truthset, Scott has spent years exposing a problem that sits at the heart of modern advertising: the vast majority of audience data flowing through digital and CTV ecosystems is far less accurate than marketers assume.Drawing on decades of experience spanning Nielsen, Exelate, and his own entrepreneurial ventures, Scott explains why advertising markets ultimately run on one thing: trust. When buyers and sellers lack confidence in audience quality, the result is friction, inefficiency, and billions of dollars in wasted media spend.The conversation takes a deep dive into Connected TV, where Scott argues that a hidden “accuracy tax” is undermining the promise of precision advertising. Much of today’s CTV targeting relies on probabilistic links between IP addresses and consumer identities—connections that, according to Truthset’s research, are often wrong the majority of the time. The result is a system where advertisers believe they are buying highly targeted audiences, while in reality they are frequently reaching the wrong households altogether.  Scott also shares a provocative thesis about the future of media: publishers, broadcasters, and streaming platforms must embrace authentication if they hope to compete with the walled gardens. Companies like Google, Meta Platforms, Amazon, and Netflix command premium advertising economics not simply because they have scale, but because they know exactly who their users are. Without authenticated audiences, much of the open internet risks becoming an increasingly commoditized marketplace of low-quality impressions and collapsing CPMs.Along the way, Scott and the hosts explore:Why trust is the foundational currency of advertising marketsHow bad identity linkages create massive inefficiencies in CTVThe historical role Nielsen played in establishing confidence in television advertisingWhy many marketing measurement systems reward cheap reach over true effectivenessThe economic case for authenticated audiences across the open webHow publishers can dramatically increase yield by prioritizing data quality over scaleWhy CPMs for truly verified audiences are likely to rise significantly in the years aheadThe need for independent standards and governance to restore confidence in digital advertisingThis episode is a powerful reminder that sophisticated algorithms, AI, and attribution systems are only as good as the data beneath them. If the underlying audience signals are wrong, every optimization built on top of them becomes suspect.For marketers, publishers, and technology providers alike, Scott makes the case that the future of advertising belongs to those who can prove that their data is accurate—and earn the trust that makes markets work.

The independent infrastructure era may be ending. In this inaugural Signal Break, we unpack one of the most consequential AdTech deals in years: Publicis Groupe acquiring LiveRamp.Joined by Bob Walczak and Krish Raja, we break down what this deal really means for identity, clean rooms, publishers, UID2, systems integrators, and the future of the open internet.Is this the end of “neutral” identity infrastructure?Are HoldCos becoming walled gardens?Does agentic AI accelerate consolidation—or make it obsolete?We get into all of it.This is the first official Signal Break: rapid-response episodes covering the biggest shifts happening across AdTech, AI, media, and infrastructure in real time. Enjoy!

What if marketing’s biggest problem isn’t a lack of data… but a lack of discipline?In this episode of Signal & Noise, we sit down with Greg Stuart, CEO of the Marketing + Media Alliance (MMA), for a deep, unfiltered conversation on why marketing still struggles to earn trust—and what it will take to fix it.Greg has spent the last several years rebuilding MMA into a global force focused on one core mission: turning marketing from a field driven by opinions, proxies, and vendor narratives into a real profession grounded in science, evidence, and predictable outcomes. This conversation is a hard reset.Because despite more dashboards, more tools, and more AI than ever, most marketing organizations still can’t answer the one question that matters:Is this actually making better decisions—and driving real business impact?The “Age of Opinion” is EndingGreg argues that marketing has operated for decades without a codified body of knowledge—unlike finance, medicine, or engineering. And until that changes, trust from the C-suite (and especially the CFO) will remain fragile.Measurement ≠ Better DecisionsOnly ~30% of marketers trust their KPIs enough to use them for strategyOnly ~29% can trace decisions back to dataJust ~22% describe their analytics capabilities as robust The problem isn’t dashboards. It’s decision-making maturity.The Attribution IllusionFrom last-click to MMM, Greg breaks down why most measurement frameworks still fall short—and why marketing continues to struggle to prove value in financial terms that CFOs actually believe.AI Won’t Save Broken FoundationsAI doesn’t create truth—it reflects patterns. If your assumptions, metrics, and operating model are weak, AI will simply scale those weaknesses faster.Why Marketing Lacks Trust (and How to Fix It)No standardized “science” of marketingOverreliance on vendors and proxiesWeak linkage to financial outcomesA discipline still driven too often by narrative over evidenceMarketing’s credibility problem is structural, not cosmeticMeasurement maturity is organizational—not just technologicalCFO trust is the ultimate test of marketing effectivenessAI is a force multiplier—but only if the fundamentals are soundThe future belongs to teams that move from reporting → experimentation → evidence → predictionThis isn’t another conversation about dashboards, tools, or tactics.It’s about whether marketing can evolve into something more rigorous, more trusted, and more predictable—or whether it continues to operate as a function driven by opinion, intuition, and fragmented incentives.If you’re a CMO, operator, or builder trying to navigate measurement, attribution, and AI… this episode will challenge how you think about all of it.Watch the full episode and join the conversation.#SignalAndNoise #Marketing #AI #Attribution #Measurement #CMO #AdTech #MarTech🔑 What We Cover💡 Key Takeaways🎯 Why This Episode Matters

For the better part of two decades, the buy-side controlled the game.Data. Decisioning. Optimization. Margin. Publishers? Commoditized. Intermediated. Squeezed.But that era may be ending.In this episode, Joe Root (Co-Founder & CEO, Permutive) returns to Signal & Noise with a sharper—and far more disruptive—thesis: AI is shifting the center of gravity of advertising back to the sell-side.We unpack what happens when:Decisioning moves closer to the dataSignal-rich environments outperform identity graphsAnd publishers stop selling impressions… and start selling outcomesBecause if the most valuable data lives on the sell-side—and AI can act on it in real time—then the entire AdTech stack gets rewritten.The Death of the “Buy-Side-First” InternetJoe breaks down why the traditional model—where DSPs optimize against thin, degraded signals—is fundamentally broken. By the time an impression reaches the bidstream, most of the signal is already gone. The result? Poor targeting, wasted spend, and a race to the bottom.The Rise of Sell-Side IntelligencePermutive’s approach flips the model: decisioning happens at the edge, inside publisher environments, where the richest behavioral and contextual data actually exists. This isn’t just better targeting—it’s a different architecture.From Curation to AI-Driven OutcomesWhat started as curation and probabilistic targeting is evolving into something bigger:→ Real-time prediction→ Continuous optimization→ Outcome-based executionWe explore how AI turns fragmented signals into scalable performance—and why this unlocks a new commercial model for publishers. The “Outcomes Era” ExplainedSelling impressions is easy. Selling outcomes is hard.Joe explains what actually has to change—technically and commercially—for publishers to move from CPMs to measurable business results. Agency Business Model ResetAs AI erodes the billable-hours model, agencies are being forced into a new role:→ Investment managers→ Principal traders→ Outcome ownersWe dig into how this shift is reshaping incentives, margins, and how media gets bought.Agentic Trading & the Future of the MarketIf both buyers and sellers deploy AI agents, what happens next?Do auctions disappear—or get demoted?Does allocation move upstream—before an impression is ever served?And who wins when media becomes negotiated instead of auctioned? This isn’t a conversation about incremental optimization.It’s about who controls the advertising system in an AI-driven world.Because if Joe is right:DSP-centric decisioning gets abstractedSSPs and publishers gain leverageAnd the open web—long written off—may have its strongest comeback yetThe future of advertising won’t be defined by who buys impressions fastest.It will be defined by who controls signal, decisioning, and outcomes closest to the user.And for the first time in a long time… that might be the sell-side.

Most companies don’t fail at strategy. They fail at execution=.In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Tom Amies-Cull—a seasoned operator who has spent two decades inside the most complex, high-pressure agency environments, including senior leadership roles across IPG, Dentsu, and Kinesso.This isn’t a conversation about AdTech plumbing.It’s about something far more fundamental—and far more broken:How organizations actually work.Or more accurately… why they often don’t.Drawing from years inside the machine, Tom unpacks the uncomfortable truth behind transformation in large, matrixed organizations:It’s not a strategy problem. It’s a coordination problem. It’s a leadership problem. It’s an operating model problem.As he puts it: “Transformation usually fails not because companies lack strategy, but because they can’t convert intent into coordinated behavior.”This is a candid, sometimes blunt breakdown of what actually gets in the way of change:Why most “transformations” are just reorgs in disguiseHow internal politics quietly kill executionThe real reason employees aren’t change-resistant—they’re resistant to bad changeWhy strategy decks and org charts are not operating modelsHow unclear decision rights create organizational paralysisThe hidden role of middle management as the “connective tissue” of executionWhy leadership teams say they want accountability—but often avoid it in practiceThere’s a lot of industry noise right now about agencies evolving into platforms, operating systems, and AI-powered machines.Tom brings this conversation back to reality:Most organizations are further away than they think.Not because the vision is wrong—but because the underlying systems (people, incentives, culture, decision-making) aren’t built to support it.The result?Pockets of excellence… held together by heroic effort, not scalable design.Everyone is talking about AI.But Tom reframes it:AI isn’t a technology problem.It’s an operating model and leadership problem.AI can accelerate planning, production, and activation—but it cannot fix:Fragmented P&LsMisaligned incentivesPoor leadership behaviorsBroken decision-making structuresIf those don’t change, AI just makes dysfunction happen faster.We also explore why indie agencies and PE-backed firms may have an edge right now:Less structural debtFaster decision-makingClearer accountabilityStronger focus on value creationWhile legacy holdcos wrestle with complexity, challengers are moving faster—and with purpose.This episode is about closing the gap between:What companies say they are…and what they are actually capable of doing.Because in today’s environment, speed matters.Clarity matters.Execution matters most.Agency transformationOperating models and org designLeadership in complex organizationsAI’s real impact on the industryThe future of holding companies…this is a must-listen.📩 Connect with Tom:Find him on LinkedIn or through his advisory work (linked in show notes)🎧 Follow Signal & Noise:Subscribe for more unfiltered conversations with operators shaping the future of media, advertising, and AI.

What happens when AI stops being a tool—and starts redefining what work actually is?In this episode of Signal & Noise, Brett House and Rio Longacre sit down with Jennifer Borchardt—UX leader, systems thinker, and newly minted Signal & Noise Executive Voice contributor—to unpack one of the most urgent questions of our time: What does AI mean for jobs, identity, and society itself?Drawing on decades of experience at firms like Sapient, Slalom, Wells Fargo, and U.S. Bank, Jennifer brings a rare perspective that blends design, behavioral science, and real-world systems thinking. This isn’t a surface-level conversation about productivity gains—it’s a deep dive into the structural shifts already underway.Together, they explore:Why the labor-based economy may be fundamentally incompatible with AGIThe rise of the “hyphenate worker”—and the slow death of specializationHow AI is unbundling work, eliminating entry-level pathways, and reshaping career trajectoriesThe uncomfortable truth about who benefits—and who gets left behindWhy most companies are still wildly unprepared, despite the hypeThe growing tension between innovation, regulation, and power concentrationAnd the deeper question few are asking: If work disappears, what happens to meaning, identity, and purpose?Jennifer also reacts to major industry frameworks, including the OpenAI “Industrial Policy for the Intelligence Age” and the Stanford University AI Index, highlighting the gap between bold policy visions and real-world human impact.This episode is equal parts optimistic and unsettling. Because while AI promises unprecedented productivity and wealth creation, it also forces us to confront a harder reality:Work isn’t just income. It’s identity. And we’re about to rewrite both.🎙️ About Jennifer BorchardtJennifer is a UX and digital transformation leader who has spent her career at the intersection of design, technology, and human behavior. She recently joined Signal & Noise as an Executive Voice contributor, where she explores the societal implications of AI and the future of work.📖 Companion ArticleDon’t miss Jennifer’s long-form piece on Signal & Noise:“Architecting Resilience in the Intelligence Age” — a deeper exploration of the ideas discussed in this episode.If you’re building, hiring, leading—or just trying to stay relevant—this conversation is required listening.Because AI isn’t just changing how we work. It’s changing why we work.

This compilation episode captures the final day of POSSIBLE 2026 in Miami — where the tone shifts from hype to clarity. Filmed entirely on-site, these conversations reflect what leaders actually think after three days of meetings, launches, and late-night debates.The signal coming out of Day 3 is clear: The industry is moving from tools → systems, from workflows → agents, and from execution → orchestration. This is where AI stops being a feature — and starts becoming infrastructure.Who’s Featured:- Mano Pillai — Co-CEO & Co-Founder, HyperMindZ: Why AI needs a control layer to manage autonomous systems at scale.- Anthony Dominguez — Senior Director, Multichannel Marketing, Orange142: The reality of multichannel execution and why coordination is still broken.- Ian Maier — GM, AdTech, Hightouch: How the composable CDP model is reshaping activation and challenging legacy stacks.- Laura Foster — SVP, Marketing, GumGum: Moving beyond targeting to moment + mindset as the real driver of performance.- Michael Akkerman — Chief Business Officer, Digital Turbine: The untapped opportunity in in-app media and the importance of relevance.- Luc Benyon — Marketing Director at Adsquare: How platform dynamics and buyer behavior are shifting in a fragmented ecosystem.- Sebastian Pinzon — Data & AdTech Strategist: Why interoperability and data infrastructure are becoming non-negotiable.- Joanna Drews — Co-Founder and CEO at HyphaMetrics: Bridging strategy and execution in a rapidly changing landscape.- Joshua John — Head of DSP Strategy, at Yahoo!: The future of DSPs in an agentic, automated workflow world.- Crystal Wallace — COO at Omnicom's Kinesso: The gap between transformation strategy and real execution.- Adam Woods — Chief Product Officer, Incubeta: Rebuilding the agency model around AI-native operating systems.Key Themes* Agentic AI and autonomous media execution* Control layers, governance, and orchestration* The collapse of legacy AdTech workflows* From point solutions → integrated systems* Why timing, context, and signals matter more than everFinal Thought: Day 3 wasn’t about what’s possible. It was about what’s already happening —and how fast the rest of the industry needs to catch up.

Day 2 of POSSIBLE in Miami was Signal & Noise at full speed—filming live from the Press Room, sitting down with some of the sharpest operators across adtech, martech, and AI. If Day 1 was about setting the stage, Day 2 was about how it actually works—the systems, tradeoffs, and rewiring happening underneath the industry.Here’s who we spoke with—and what they unpacked:Adam Heimlich (Chalice AI) — Agentic media buying, containerized decisioning, fixing broken DSP modelsAna Mourão (Black & Decker) — First-party data activation, martech–adtech convergence, retail mediaMike Finnerty (Mutinex) — AI-powered MMM, incrementality at speed, killing “great but late” measurementXander Kotsatos (Aqfer) — Zero-copy data, infrastructure economics, data pipelines as the new moatDavid Nyurenberg (InterMedia Advertising) — Digital evolution, agency strategy, performance realitiesDoug Lauretano (Tuple) — DSP reinvention, supply path inefficiencies, unlocking “lost” inventoryNeej Gore (Zeta Global) — Identity graphs, decisioning systems, AI as the marketing brainSara Martinez (Tracer) & Vinny Rinaldi (Hershey’s) — Semantic layers, measurement clarity, brand executionJill Randell (Fuse) — AI for insights, fixing broken dashboards, trust in dataTom Koch (TwelveLabs) — Video understanding AI, multimodal models, unlocking unstructured data Todd Ulise (Nomix Group) — AI, Synthetic Creators, and Commerce at ScaleThe big themes from Day 2:This wasn’t surface-level AI hype. The throughline was clear:AI is moving from tools → systems → decisioning layersData is still the bottleneck (and the battleground)The stack is collapsing into “operating systems”Measurement is being rebuilt from first principlesThe open web vs. walled gardens fight is evolving—not endingAcross every conversation, one idea kept coming up:The winners won’t just use AI—they’ll re-architect around it.From agentic trading models to real-time MMM, from identity graphs to video intelligence, Day 2 showed what the industry looks like when you zoom past the buzzwords and into the machinery.And it’s clear:The future of marketing isn’t just automated—it’s negotiated, orchestrated, and deeply data-native.This compilation brings together the sharpest insights, debates, and moments from the floor.👉 Want the full conversations?Each interview is available individually on our YouTube channel.About Possible 2026Possible is one of the fastest-growing gatherings in media, marketing, and technology—bringing together brands, platforms, agencies, and innovators to define what’s next. More from Day 3 coming soon.

Recorded live from the MadConnect Mansion in Miami, this special Signal & Noise episode captures Day 1 of Possible 2026—bringing together some of the sharpest operators across advertising, media, data, and AI.Across a full day of rapid-fire interviews, Rio Longacre, Brett House, and Krish Raja sat down with industry leaders to unpack what’s actually happening beneath the surface of the hype cycle.Dave Rosner — On the untapped power of publisher data and the buy-side blind spotPete Blackshaw — On brand trust in an AI-driven discovery landscapePatrick Duggan — On AI monetization and the race to profitabilityErez Levin — On ad quality, attention, and the race to the bottomAubriana Alvarez Lopez — On orchestration, AI, and fixing the adtech operating modelNathan Lindberg — On gaming, creators, and the next media frontierMK Marsden — On AI’s impact on sales and the future of the revenue engineSarah Caputo — On CTV monetization, frequency, and the viewer experienceFrom AI-driven operating models and monetization strategies to CTV fragmentation, ad quality, and the rise of new creator ecosystems—Day 1 of Possible made one thing clear:The industry isn’t lacking innovation—it’s struggling to operationalize it.This compilation brings together the sharpest insights, debates, and moments from the floor.👉 Want the full conversations?Each interview is available individually on our YouTube channel.Possible is one of the fastest-growing gatherings in media, marketing, and technology—bringing together brands, platforms, agencies, and innovators to define what’s next. Day 1 set the tone: AI is here, but execution is the real battleground.More from Day 2 coming soon.

What does it actually mean to be “full stack” in a world where AI is starting to write the code for you?In this episode of Signal & Noise, Lucas Longacre sits down with Viktor Williamson for a deep, practitioner-led conversation on the evolution of software engineering—from fundamentals to the fast-emerging agentic future.This marks Lucas’s second long-form appearance on S&N and builds on his work as an Executive Voices contributor, bringing a product-led perspective to a rapidly shifting technical landscape.Together, Lucas and Vik break down:What “full stack” actually means—and why it’s becoming more critical than everHow modern frameworks like Next.js are reshaping development paradigmsWhy performance, flexibility, and cross-functional thinking are redefining engineering rolesThe real impact of AI and agentic coding on how software gets builtWhy engineers are shifting from writing code → reviewing, guiding, and orchestrating itThe growing importance of accessibility, security, and human-centered design in modern systemsBut this isn’t just a technical conversation—it’s a philosophical one.As AI accelerates development, the question isn’t whether engineers will be replaced. It’s whether they can evolve fast enough to stay relevant.“We’re not doing less work. We’re being asked to do more—with higher expectations and faster timelines.” From personal projects and “disposable apps” to the future of software as hyper-personalized infrastructure, this episode explores where the craft of engineering is headed—and what it means to stay human in the loop.Full stack as a mindset, not just a skillsetAgentic coding and the rise of AI-assisted developmentFrom builders to orchestrators: the new role of engineersPersonal software, micro-apps, and the death of bloated platformsAccessibility and security as non-negotiablesHuman judgment in an automated worldViktor Williamson is a full stack engineer, educator, and mentor with a passion for human-centered development. With roots in front-end engineering and deep experience across the stack, Vik brings a rare combination of technical depth, communication skill, and real-world perspective on how engineers learn, build, and evolve.

Everyone agrees first-party data matters. So why is almost none of it actually showing up in media?In this episode of Signal & Noise, Rio Longacre and Brett House sit down with Rob McLaughlin, Founder & CEO of AUDIENCES, to unpack one of the biggest disconnects in modern marketing: the gap between data strategy and data activation.Despite years of investment in CDPs, clean rooms, cloud migrations, and identity graphs, less than 3% of media spend is actually informed by first-party data. That’s not a tooling problem. It’s a model problem.Rob breaks down why the industry has been stuck—and what needs to change:Why first-party data is widely understood… but rarely usedWhere activation actually breaks (hint: it’s not just tech)How data movement, cost, and org friction quietly kill executionWhy brands are still paying a “tax” to use their own dataAnd why the future isn’t more platforms—it’s less movement, more signalMarketers didn’t fail to invest. They failed to connect.Most brands now have:Cloud infrastructureMassive first-party datasetsSophisticated media partnersBut the “last mile”—getting that data into live campaigns—is still fragmented, expensive, and slow. The result? Campaigns ship without it. Rob’s thesis is simple—but disruptive: Stop moving data. Start moving signals.AUDIENCES flips the model:Keep data inside the brand’s cloudActivate directly from the sourceEliminate onboarding, duplication, and unnecessary costThis isn’t just cleaner architecture—it changes:Privacy dynamics (no data copying)Cost structure (no per-record tax)Speed of activation (real-time, not batch)Forget the buzzwords. This is where it works:Suppression → Stop wasting spend on existing customersSeed audiences → Outperform platform-native targetingLookalikes → Scale what actually drives valueRetail media & supply-side data → Unlock real reachAnd yes—brands are still getting retargeted with products they already bought.This episode goes beyond tactics into structure:Why the future agency looks more like an operating system than a service layerWhy identity + infrastructure is becoming the real differentiatorHow the balance of power is shifting back toward data ownersAnd why agencies without deep data integration risk becoming assemblers—not operators“CDPs are irrelevant in a cloud-native world.”“There should not be a tax on activating your own data.”“The problem isn’t that brands lack data—it’s that they can’t use it.”CMOs and Heads of Media trying to unlock real performance from 1P dataData & platform leaders stuck between cloud investment and activation realityAgency leaders navigating the shift from services → infrastructureAnyone tired of hearing “first-party data is the future” without seeing resultsExplore AUDIENCES: https://weareaudiences.comConnect with Rob McLaughlin: https://www.linkedin.com/in/robanalytics/If you’re building at the intersection of data, media, and AI—this is your playbook.Subscribe to Signal & Noise on:SpotifyApple PodcastsYouTube🔍 What You’ll Learn⚡ The Big Idea: The Last Mile Is Broken🧠 A Different Model: Signals, Not Datasets🚀 Where First-Party Data Actually Wins🏗️ What This Means for Agencies & HoldCos💥 Hot Takes from Rob🎯 Who This Episode Is For🔗 Learn More🔊 Listen & Subscribe

Everyone says they want growth. Very few organizations are actually built to deliver it.In this episode of Signal & Noise, we sit down with George Musi—former executive across Publicis, WPP, IPG, and Horizon, now an advisor to Fortune 500 and high-growth companies—to unpack why growth consistently breaks inside large organizations.This is not a conversation about frameworks or slideware.It’s about what actually happens when strategy hits reality.George brings an operator’s lens to one of the biggest disconnects in the industry right now: companies are overflowing with ideas, AI roadmaps, and transformation narratives—but still struggle to execute consistently. Why growth is structurally hardGrowth doesn’t fail because of a lack of strategy—it fails because of how organizations are wired. Incentives, silos, and decision-making systems break execution long before ideas do.The HoldCo → Operating System shift (and what’s real vs narrative)Every agency claims to be building an “operating system.”George explains why most of these are still fragmented point solutions—and what a true system actually requires.Why agencies are colliding with consultancies and platformsAs agencies move into data, tech, and integration, they’re stepping directly into the territory of firms like Accenture and Deloitte—while also competing with platforms like Google and The Trade Desk.AI is not a tool problem—it’s an operating model problemMost companies are layering AI on top of broken systems.The result: more noise, not more output.Real impact requires rebuilding how knowledge, workflows, and decisions actually operate.The real future of the agency modelThe FTE-based, labor-driven model is under pressure.What replaces it? Outcome-based partnerships, deeper expertise, and a shift toward “growth architects” over execution vendors.Why institutional knowledge is the ultimate advantageData is commoditized. Models are commoditized.The real differentiator is the ability to capture, retain, and compound organizational knowledge over time—and most companies are terrible at it.Strategy isn’t the problem. Execution systems are.AI amplifies what already exists—it doesn’t fix it.The agency model is being reshaped from labor → leverage.The winners will be those who build systems of intelligence, not just tools.Growth will be owned by those who can connect strategy, operations, and execution into a single system.George also joins Signal & Noise as part of our Exec Voices platform—bringing a no-BS perspective on growth, go-to-market, and what actually works inside complex organizations.If you care about where agencies, consultancies, and platforms are heading—and what it really takes to scale—this is a must-listen.Listen on Spotify | Watch on YouTube | Read more at signalandnoise.aiWhat we cover:Key takeaways:

Most B2B companies don’t fail because the product is bad.They fail because the system around it is broken.In this episode of Signal & Noise, we sit down with Marc Sabatini, Co-Founder and Chief Commercial Officer at HighSignals, to break down what Brett has been calling the GTM Slop Problem—and why so many launches stall before the market even has a chance to decide.Marc has spent 30+ years operating at the intersection of product, sales, marketing, and customer success—the exact place where strategy either turns into revenue… or quietly falls apart. This is not a theory episode.This is how go-to-market actually works—or doesn’t—in the real world.1. Why GTM breaks before the market even decidesThe biggest failure point isn’t competition.It’s internal:Misaligned teamsFuzzy narrativeNo shared systemNo clear ICPAs Marc puts it: “It’s not just slop from inexperience. It’s slop from lack of coordination.” 2. The Six Dimensions of GTM (and where they fall apart)We walk through the six dimensions every company thinks they have dialed in:Narrative (not messaging—commercial logic)ICP & targeting (focus vs. “sell to everyone”)Competitive readinessOffer & proofField enablementActivation & measurementThe takeaway:Most companies don’t have weak pieces.They have weak connections between the pieces.3. Problem Market Fit vs. Product Market Fit vs. Platform Market FitOne of the most important frameworks in the episode:Problem Market Fit → You can sell, but it’s messyProduct Market Fit → You can scalePlatform Market Fit → You can compoundMost companies get stuck in the first phase—generating revenue without ever building a system that scales.4. Why “great products win” is a mythThe uncomfortable truth:The best product rarely wins.The best go-to-market does.Even strong products fail when:Narrative is unclearProof is weakSales is improvisingCustomer success is disconnectedOr simply:Too much activity. Not enough coherence.5. Partner-Based Buying is changing everythingBuyers aren’t buying alone anymore.Agencies, SIs, cloud partners, and ecosystems are now:Influencing decisionsValidating vendorsActing as gatekeepersWhich means:You’re not just selling to the end buyer.You’re selling to the entire buying system.And that changes your proof stack completely.6. Why most companies fail entering the US marketMarc breaks down a common pattern:Too broad ICPWeak local proofMisread buyer expectationsActivity without tractionThe result:Burned time, burned budget, and burned field trust.7. The real job of GTM: building a system, not running campaignsThis is the core idea of the episode:GTM is not marketing.GTM is not sales.GTM is not a launch plan.It’s a connected commercial system.And when that system breaks:Messaging gets blamedSales gets blamedProduct gets blamedBut the real issue is lack of alignment and orchestration.There’s more product being built right now than ever before.AI has lowered the barrier to creation.But it hasn’t solved:PositioningDifferentiationCommercial executionIf anything, it’s made the problem worse.More products.More noise.More GTM slop.Founders trying to turn product into revenueCROs, CMOs, and GTM leaders fixing broken systemsAnyone launching B2B SaaS or AI productsOperators tired of “more activity” being the answerIf there’s one idea to walk away with, it’s this:A launch is not ready just because the product is ready.It’s ready when the system around it is coherent.Most companies never get there.

In Part 1, we talked about bots. In Part 2… we follow the money.Brett and Rio sit down again with Dr. Augustine Fou, and this time the conversation goes deeper—and gets a lot more uncomfortable. Because the real issue isn’t just fraud. It’s the system that quietly profits from it.We break down what actually happens between the moment a marketer places a bid and the moment a publisher gets paid. The gap is bigger than most people realize. In one example, a $1.50 CPM turns into just $0.15 for the publisher. In another, increasing your bid doesn’t get you better inventory—it just means someone in the middle keeps more of your money. And a lot of what gets reported as “performance” can be completely fabricated—clicks, conversions, even analytics data .This episode is about that hidden layer most teams never see: take rates, pass-through opacity, spoofed supply, and the growing gap between what advertisers pay and what publishers actually receive.Then we turn to what’s coming next: agentic AI.Because if your inputs are broken, automation doesn’t fix it—it just scales the problem faster. The same systems that already struggle with transparency are now being handed more autonomy, more budget, and more control.We get into why blended averages hide the truth, why the industry’s long-standing “1% fraud” narrative doesn’t hold up, and why so many optimization systems are quietly steering budgets toward cheaper, lower-quality inventory. We also unpack the difference between “attention” and actual human engagement—and why so much of what’s sold today is closer to performance theater than real outcomes.By the end, this isn’t just a critique—it’s a playbook.If you’re a marketer, this episode will change how you think about where your dollars are going, who’s extracting value in the supply chain, and what you can do—right now—to take back control.Because the real question isn’t:“Is there fraud?”It’s: “Who’s getting paid—and how much are they taking?”

Careers in AdTech don’t follow a straight line. They follow the market.In this episode of Signal & Noise, we sit down with Evgeny Popov, a global media operator whose career cuts across publishers, agencies, AdTech platforms, and now television data—from News Corp to Lotame, Verve, and today at Samba.This isn’t just a career story.It’s a map of how the industry actually works.Because Evgeny has seen every layer of the ecosystem up close—how publishers monetize, how agencies operate, how data platforms scale, and how companies position themselves for exits. And now he’s sitting at the center of the next major shift:the transformation of television into a data-driven, measurable, and programmable channel.1. From engineer to global AdTech operatorEvgeny didn’t start in media—he started in engineering. That technical foundation became a career advantage as the industry shifted toward data, automation, and programmatic systems. 2. Building a career across every layer of the ecosystemPublishers → agencies → DSPs → data platforms → CTVThis wasn’t random. It created a rare, full-stack perspective on how media actually functions—and where the leverage sits.3. What actually drives successful exits in AdTechEvgeny has been part of multiple acquisitions. The takeaway:It’s not just about product. It’s about timing, signal, and positioning within the market.4. Why relationships matter more than people admitIn an industry that constantly reinvents itself, networks compound.Or as Evgeny puts it: “I collect good humans.” 5. Inside Samba and the rise of ACR dataWe break down how Automated Content Recognition (ACR) actually works—and why it’s becoming one of the most important data signals in the CTV ecosystem:What’s actually being watched (not just served)Cross-platform viewership across streaming, linear, and gamingA deterministic layer in an increasingly fragmented landscape6. The real state of CTV (beyond the hype)CTV is growing fast—but measurement is still broken.Fragmentation, inconsistent currencies, and platform silos are holding the market back.7. Television is becoming a data problemNot a media problem.Not a creative problem.A data + identity + measurement problem.And whoever solves that layer controls the future of TV advertising.We’ve spent the last decade talking about:ProgrammaticIdentityData platformsBut television is where all of it converges.And for the first time, we’re seeing:Deterministic signals (ACR)Cross-platform measurementReal competition for the “currency” layerThis isn’t just the evolution of TV.It’s the reconstruction of the largest media channel in the world.AdTech operators thinking about where the market is headingAnyone working in CTV, streaming, or measurementEarly-career folks trying to understand how to actually build a career in this industryPeople who want the real version of how this ecosystem works—not the slideware versionIf you strip everything else away, this episode comes down to one idea:The people who win in this industry aren’t the ones who stay in one lane.They’re the ones who understand how the entire system connects.Evgeny is one of those people.

In this episode of Signal & Noise, we sit down with Leighton Welch (CTO) and Sarah Martinez (CCO) from Tracer to unpack a fundamental shift happening across enterprise data, marketing, and advertising:The stack is being rebuilt around data—not applications.And at the center of that rebuild? The semantic layer.This conversation goes beyond the usual “data unification” talking points. Instead, we break down the five structural shifts reshaping enterprise data strategy right now—and why they matter more than ever as AI moves from experimentation to execution.Tracer provides a practical lens into this transformation. Not as another dashboard or point solution, but as a system designed to solve a harder problem: How do you create shared, trusted business logic across fragmented systems so both humans and AI can act on the same truth?1. Why enterprise data strategy is suddenly back on the front burnerAI didn’t create the data problem—but it exposed it. As Leighton puts it, AI is forcing organizations to prioritize initiatives they should have tackled a decade ago, from centralized data ownership to consistent definitions. 2. The five shifts redefining the stackSemantic layers as the new business logic layerWarehouse-native architecture replacing SaaS silosZero-copy activation reducing data duplicationGovernance becoming infrastructure—not complianceAI readiness as the new forcing function3. The semantic layer as the control plane for AIIf AI is the operating layer, then definitions, context, and trust become the system of control. Without a shared “data dictionary,” agents don’t just fail—they amplify inconsistency.4. Why monolithic SaaS is under pressureEnterprises are moving away from copying data into every tool. The warehouse is becoming the system of record, and everything else is being forced to justify its existence.5. The real problem: not data, but meaningMost companies don’t lack data—they lack agreement on what that data actually means. Tracer’s approach focuses on turning raw data into reusable, governed business logic that can power decisions across teams.6. AI readiness isn’t about models—it’s about foundationsClean data, consistent taxonomy, shared definitions, and governance aren’t “nice to have.” They are prerequisites. Without them, AI becomes a very fast way to make very bad decisions.For years, the industry debated identity vs. platforms, CDPs vs. composability, centralization vs. federation.But that’s not the real shift.The real shift is this: Data is no longer an input to the system.It is the system.And the companies that win won’t be the ones with the most data—they’ll be the ones with the most trusted, reusable, and operationalized context.CMOs and marketing leaders trying to make AI realData and analytics teams dealing with fragmented stacksAdTech/MarTech operators navigating warehouse-native architecturesAnyone tired of waiting 6 months for insights that are outdated on arrivalIf you take one thing from this episode, it’s this:AI doesn’t fix bad data. It exposes it.And the semantic layer is how you fix it.

The CDP isn’t dead—but it’s definitely not what it used to be.In this episode, Rio Longacre and Brett House sit down with Dale Renner, CEO of Redpoint Global—and one of the earliest architects of the space—to revisit the rise, fragmentation, and uncertain future of the CDP.From helping shape the first-ever CDP deal to navigating today’s fractured landscape, Dale unpacks what actually happened—and where things went sideways .They get into:Why the category splintered across identity, segmentation, and activationThe real tension between marketing, IT, and data ownership—and why most CDPs failed to bridge itHow “everyone became a CDP,” turning the category into a mile-wide, inch-deep messWhy many companies ended up with multiple CDPs—and still didn’t solve the problemThe hidden truth: without high-quality data and identity, personalization is just noiseAnd most importantly—what comes next.As AI reshapes the stack, Dale makes a clear bet:The future isn’t vendor-built platforms or pre-packaged agents.It’s data readiness, composable architectures, and company-owned agentic layers—built on top of systems that can actually handle identity, scale, and complexity.Because in the end, this was never about CDPs. It was always about the data.

AdTech has built some of the most sophisticated technology in the digital economy — and some of the most forgettable marketing.In this episode of Signal & Noise, we sit down with Joe Zappa, Founder & CEO of Sharp Pen Media, to unpack a hard truth the industry rarely confronts:You can’t outsource belief.For decades, AdTech companies have treated marketing as something downstream — polish it, package it, delegate it. But Joe argues that’s exactly where things go wrong. When CEOs hide behind feature lists, jargon, and generic positioning, marketing becomes interchangeable. And in a crowded ecosystem where everyone claims better targeting, better measurement, and better AI, invisibility becomes the real risk.Joe makes the case that the CEO must be the chief evangelist — not a mascot, not a quote-approver, but an active communicator who can clearly articulate:What’s broken in the industryWhat they believe about the futureWhy their company existsAnd why anyone should careWe go deep on:Why AdTech messaging collapses into samenessThe difference between product speak and narrativeHow to build a simple, usable messaging “Bible”Why controversy is often safer than invisibilityThe collapse of institutional gatekeepers — and what that means for foundersHow AI can amplify clarity — or create “slop cannons”Why humanities training may be more valuable than ever in the AI eraThis conversation isn’t just about marketing tactics. It’s about leadership, conviction, and attention in a world where distribution is democratized and authenticity matters more than ever.If you’re a founder, CEO, CMO, product leader, or operator in AdTech, MarTech, or media — this episode will challenge how you think about voice, visibility, and responsibility. Because in 2026, you don’t win by having the best deck. You win by having the clearest belief.

Lucas Longacre officially joins Signal & Noise—and in his debut episode as an Executive Voices contributor, he starts exactly where great product work begins: in the mess.In this conversation, Lucas sits down with Zach Grumet—product leader, operator, and one of the key figures behind Lucas’s own transition into product—to unpack what it actually means to “structure the ambiguity.”This isn’t a conversation about frameworks or buzzwords. It’s about the real work:Why product managers don’t “ship features”—they own the messHow unclear problems, bad communication, and organizational friction kill good productsThe difference between product managers and actual product leadersWhy most teams solution too early—and miss the problem entirelyAnd how AI is quietly rewriting the rules of product development in real timeAlong the way, they get into the uncomfortable truths: failed decisions, broken processes, internal chaos—and why those moments are where real product thinking is forged.From reducing onboarding friction to predicting parking enforcement patterns (yes, really), Zach brings battle-tested lessons from FinTech, HealthTech, and SaaS—while Lucas connects it to a new reality where prototyping happens in hours, not quarters.But beneath it all is a bigger question: If AI accelerates everything… what actually matters more?This episode is about clarity in a world that’s only getting noisier. And it’s just the beginning.

Programmatic advertising has spent the last 15 years optimizing for one thing: speed.But somewhere along the way, we lost something more important—control, transparency, and true decisioning intelligence.In this episode of Signal & Noise, we sit down with Adam Heimlich, Founder & CEO of Chalice AI, to unpack what happens when an operator who spent decades inside the system decides to rebuild it from the ground up.Adam’s perspective is different. He’s not theorizing about programmatic—he ran it. He understands the incentives, the inefficiencies, and the architectural limitations of RTB and DSP-driven buying. And now he’s building a new model.We cover:Why RTB infrastructure is fundamentally constrained by legacy “pipes”- How Chalice is using containerized decisioning to move logic closer to the bidstream- What the Agentic RTB Framework (ARTF) actually is—and why it mattersWhy AI agents may reshape how media decisions are made (and who controls them)The shift from platform-centric buying → modular, agent-driven ecosystems- Why data is commoditized—but modeling and service are notThe real implications of agentic trading and AI-native marketplacesWe also go beyond the tech:Adam’s transition from agency operator to founder- Building Chalice alongside his partner Ali ManningThe reality of startup life vs. the mythologyAnd yes… the philosophy behind AdTech shitpostingThis is a conversation about more than bidding mechanics. It’s about whether the entire architecture of digital advertising is about to change—and who wins if it does.If you care about where programmatic is actually heading—not just what vendors are selling—this one is worth your time.👇 Subscribe for more Signal & Noise🌐 signalandnoise.ai🎙️ Available on Spotify, Apple, and YouTube

What if dashboards are dying—and analytics is about to feel more human? In this episode of Signal & Noise, hosts Brett House and Rio Longacre sit down with Adam Greco, one of the most influential voices in digital and product analytics, to unpack a provocative idea: Vibe Analytics.Adam—former Omniture and Amplitude leader and current Product Evangelist at Hightouch—argues that the future of analytics won’t be defined by dashboards, SQL queries, or rigid reporting tools. Instead, it will be driven by natural language, AI-powered interfaces, and warehouse-native architectures that let teams ask questions the way humans think.Together, we explore:- What “Vibe Analytics” actually means—and why it’s more than a buzzwordWhether traditional analytics platforms like Adobe, Amplitude, and Tableau are at risk- How AI and conversational UX could democratize analytics (and de-specialize it)- What this shift means for analysts, marketers, CMOs, and data teams- Why warehouse-native stacks built on Snowflake and Databricks are foundational to what comes next- We also dig into real-world implications for measurement, attribution, personalization, and data collaboration—and debate whether this moment represents evolution… or extinction… for legacy analytics tech.If you work in analytics, marketing, product, or data—and you’ve ever felt constrained by dashboards—this is a conversation you don’t want to miss. Enjoy!

Every year, leaders from across advertising, technology, and media gather in San Francisco for RampUp, the annual conference hosted by LiveRamp. Over the past decade, RampUp has become one of the most influential events in the AdTech ecosystem—bringing together brands, agencies, publishers, data providers, and technology platforms to discuss the future of identity, data collaboration, and responsible advertising.LiveRamp sits at the center of that conversation. The company built its reputation as a pioneer in identity resolution—helping marketers connect fragmented consumer signals across devices, platforms, and channels in a privacy-conscious way. Today, LiveRamp’s technology powers a broad data collaboration ecosystem that allows organizations to safely match, analyze, and activate data across partners, platforms, and clean room environments. As the advertising industry moves deeper into a world defined by privacy regulation, signal loss, and AI-driven decisioning, LiveRamp’s role as a neutral identity and data collaboration layer has only grown more important.In this special Signal & Noise episode, Rio Longacre and Krish Raja kick things off with a recap of RampUp 2026, sharing their perspective on the biggest themes from the event—from the evolution of identity infrastructure to the rise of retail media networks, the increasing importance of data collaboration, and the growing influence of AI across the marketing ecosystem.The episode then features a series of conversations with some of the industry’s leading voices who attended RampUp:Shailley Singh, COO & EVP of Product at IAB Tech Lab, discussing the future of industry standards, interoperability, and the technical infrastructure shaping digital advertising.Leigh M. Freund, CEO of Network Advertising Initiative (NAI), on privacy, regulation, and the evolving role of self-governance in digital advertising.Austin Leonard, VP/GM of Dollar General Media Network, exploring the continued rise of retail media and how new entrants are building powerful commerce-driven advertising platforms.Daniel Block, Head of Corporate Business Development at Fetch Rewards, on the growing role of consumer data platforms and loyalty ecosystems in modern marketing.Scott Messer, Founder & CEO of Messer Media, offering an independent operator’s perspective on the current state—and future direction—of AdTech.Together, these conversations paint a picture of an industry that is rapidly evolving. Identity is being rebuilt. Data collaboration is becoming a core operating model. Retail media continues its explosive growth. And AI is beginning to reshape how campaigns are planned, executed, and optimized.In other words, RampUp 2026 offered a glimpse into the next phase of digital advertising—and in this episode, we separate the signal from the noise.

In this episode of Signal & Noise, Rio and Brett sit down with Crystal Santos Wallace — enterprise operator, data leader, and longtime architect of modern marketing infrastructure across global holdcos — for a candid conversation about what AI is actually doing inside agencies.Crystal has worked across the major networks and now operates at the intersection of data, identity, and transformation at Omnicom and Acxiom. She’s seen data evolve from passive record-keeping to operational truth — and now into fuel for agentic systems.Her thesis is simple but sharp: AI doesn’t fix broken data. It makes broken data louder.What We CoverFrom Platformization to Agentic Workflows:For the last decade, marketing technology has centered on “monolithic SaaS” platforms promising integration and control. Crystal argues we’re entering a new phase — not the death of platforms, but their transformation. The future isn’t fewer systems; it’s orchestrated systems, powered by agents and governed by design.Governance Is Not Optional:As AI accelerates, governance becomes existential. From model access and data leakage risks to inappropriate automated outputs, Crystal makes the case that compliance, security, and policy must evolve alongside innovation — not trail behind it. Human-in-the-loop isn’t a philosophical preference; it’s a risk mitigation strategy.Synthetic Audiences & Continuous Learning:We explore the rise of synthetic focus groups, digital twins, and always-on modeling. Used correctly, these tools compress the research cycle and create test-and-learn loops at scale. Used carelessly, they amplify bias. The difference? Data quality and disciplined inputs.The Changing Commercial Model:As AI reshapes workflows, the traditional FTE model inside agencies comes under pressure. Crystal speculates about usage-based, tokenized, and outcome-oriented commercial structures — and why the winners will balance technical literacy with strategic altitude.The Future CMO:Tomorrow’s CMO isn’t just a brand steward. They’re an orchestrator of systems, a translator between data science and business strategy, and a leader who understands enough about AI to direct it — without being consumed by it.This is a conversation about scale, identity, governance, and the pace of change. It’s also a reminder that technology doesn’t absolve us of responsibility. It magnifies it.If you’re navigating AI transformation inside an agency, a brand, or a data organization — this one’s for you.🎙️ Subscribe to Signal & Noise wherever you listen.

For decades, user experience has been built around a simple assumption: the human is the operator. We click, swipe, navigate, and tell systems what to do. But that assumption is breaking down.In this episode of Signal & Noise, hosts Rio Longacre and Brett House sit down with Drew Burdick to explore what happens when AI systems stop waiting for instructions and start acting on our behalf. As agentic AI moves from experimentation to production, UX is no longer about screens and flows—it’s about designing relationships, trust, and alignment between humans and autonomous systems.Drew brings a practitioner’s perspective on how UX must evolve when agents anticipate intent, take action across systems, and reason about outcomes. We dig into what “Agentic UX” really means, which long-held UX assumptions no longer apply, and why the next generation of interfaces may be invisible, conversational, or entirely new in form.The conversation covers emerging interaction models, transparency and control, trust calibration, failure states, and the ethical responsibilities designers inherit when machines begin making decisions. We also discuss how UX teams, designers, and organizations need to restructure skills, roles, and workflows to stay relevant in an agentic world.This episode is for designers, product leaders, and technologists grappling with a fundamental shift: when AI becomes a collaborator instead of a tool, experience design becomes one of the most strategic disciplines in the company.

The marketing industry spends more than $4,000 per U.S. household every year.Analysts estimate that 20–30% of that spend may be lost to waste, inefficiency, and outright fraud — tens of billions of dollars annually.So here’s the uncomfortable question:If everyone knows the plumbing is broken… Why does the system keep running?In this episode of Signal & Noise, Rio Longacre and Brett House sit down with Sarah Caputo & David Nyurenberg to unpack what rarely gets said out loud: the persistence of media waste isn’t just a technology problem — it’s an incentive problem.From opaque take rates and arbitrage models to CTV supply path manipulation, from procurement-driven CPM pressure to vanity metrics masquerading as performance — this conversation pulls back the curtain on how the ecosystem actually works.Sarah and David bring firsthand experience from agencies, holding companies, publishers, and the brand side. They share real stories of:Arbitrage margins north of 80%Inventory labeled one way and delivered anotherContract loopholes that block transparencyThe career risk of asking the wrong questionsAnd the quiet pressure to “not rock the boat”The uncomfortable truth? Silence is often rewarded. Transparency can be punished. But it doesn’t have to be this way.We dig into what brands can do right now — from contractual protections and audit rights to internal capability building — to regain leverage and reduce exposure to hidden inefficiencies.If you work in AdTech, MarTech, CTV, programmatic, or media buying, this episode will feel very familiar.If you’re on the brand side, it may change how you think about your next RFP.Read the companion article:👉 https://www.signalandnoise.ai/post/the-cost-of-keeping-quietSubscribe for more candid, operator-level conversations about advertising, media, technology, and the incentives shaping what’s next.No hype. No spin. Just signal.

Part 2 of this series. If you haven’t watched Part 1, start there for the core framework on aligning GTM and CX as one operating system.In this episode, we look at real-world examples of companies that either connect—or fracture—GTM and customer experience.We reference operator-driven clarity at DoubleVerify, premium ecosystem consistency at Apple, channel fragmentation in Auto, mature orchestration at Flywheel, and competitive GTM tempo from OpenAI.We also touch on ServiceNow, HubSpot, and Datadog as B2B SaaS examples of alignment done well.The throughline is simple: when GTM and CX operate as one system, growth becomes repeatable—not accidental.

GTM is not messaging. It’s the operating system that turns value into adoption.GTM is the promise you make to the market. Customer experience is the proof the customer lives with.When GTM and CX are disconnected, you get three predictable failures:Story drift: sales sells one thing, onboarding delivers another, CS explains the gapAdoption drag: the product may be good, but the experience doesn’t get users to value fast enoughTrust decay: customers don’t renew based on features, they renew based on the outcomes they felt.

Commerce media is exploding—projected to surpass $100B in US ad spend by 2028—but beneath the hype, a harder question is emerging: is this truly incremental growth, or just a rebranded tax on brand dollars?In this episode of Signal & Noise, hosts Rio Longacre and Brett House sit down with Amie Owen, Global Chief Commerce Officer at IPG Mediabrands, to cut through the noise surrounding retail and commerce media.With Amazon and Walmart controlling roughly 80-85% of U.S. retail media spend—and more than 200 retail media networks now live—brands are facing growing fragmentation, opaque measurement, and rising pressure to “pay to play” on the digital shelf.Together, we unpack:- The difference between retail media and commerce media—and why it matters- Why many brands see commerce media as both a growth engine and a brand tax- How closed-loop attribution and deterministic purchase data are reshaping media strategy- Whether retail media is truly incremental—or simply reallocating trade spend- The role of CTV, clean rooms, and commerce signals in the next wave of growth- How agencies can help brands navigate fragmentation, standardization, and measurement chaos- What AI, agentic systems, and commerce data mean for the future of media planningIn a wide-ranging discussion, Amie brings a pragmatic, operator’s perspective—grounded in real client outcomes—on how brands should think about commerce media in 2025 and beyond: where to lean in, where to push back, and how to avoid confusing scale with success.If you’re a CMO, media leader, or brand navigating retail and commerce media today, this episode will help you separate signal from noise.

The Customer Data Platform, or CDP, was supposed to be marketing’s system of record. Instead, it’s become one of the most fragmented—and misunderstood—categories in the stack.In this episode of Signal & Noise, hosts Brett House and Rio Longacre sit down with Matthew Niederberger, Founder of MarTech Therapy, for a candid, practitioner-level conversation about where the CDP market actually stands today—and where it’s headed next.Matthew brings 20+ years of hands-on MarTech experience and a global perspective from working directly with brands across Europe and beyond. Together, the group unpacks why so many CDP initiatives stall, why buyers remain confused despite a decade of “category maturity,” and why analyst frameworks like the Gartner Magic Quadrant are becoming increasingly misaligned with how marketing technology is really bought and used.This isn’t a vendor ranking episode. It’s a reality check.Topics include:Why the CDP category feels both overcrowded and incompletePlatform CDPs vs. composable stacks—and where agentic AI actually fitsThe hidden costs of monolithic ecosystems and switching frictionWhy “data quality” still matters more than architecture diagramsHow regional maturity (especially in Europe) changes buying behaviorWhat marketers should actually trust when evaluating CDP optionsWhether “CDP” survives as a standalone category—or dissolves into something else entirelyIf you’re a CMO, CIO, MarTech leader, or practitioner navigating CDP decisions in 2025, this episode will help you separate signal from noise—and avoid buying technology that looks great on a quadrant but fails in the real world.👉 Subscribe to Signal & Noise on YouTube, Spotify, and Apple Podcasts for weekly, no-BS conversations on data, tech, and AI—and what actually matters next.

In this episode of Signal & Noise, hosts Rio Longacre and Brett House sit down with Erez Levin—former Google leader, ad quality advocate, and cultural reformer—for a wide-ranging conversation about speech, norms, and the dangerous space between censorship and permissiveness.Erez has spent his career challenging broken incentives—from paid media’s obsession with outcomes over quality to workplace norms that quietly discourage responsibility. In this conversation, he turns that same lens toward culture itself, introducing his TABOO framework: a call to restore shared social boundaries around overt bigotry, dehumanization, and the endorsement of violence—without reviving cancel culture or state censorship.The discussion explores how cancel culture unintentionally weakened society’s ability to enforce real moral limits, why antisemitism has become a visible stress test for eroding norms, and how both the “woke left” and “woke right” exploit the same failures from opposite directions. Erez makes the case that social consequences are not censorship, that forgiveness must follow accountability, and that societies collapse not when speech is free—but when nothing is out of bounds.This episode isn’t about partisan politics. It’s about guardrails, courage, and what happens when no one is willing to hold the line.Topics include:- Cancel culture vs. consequence culture- Antisemitism as a warning sign, not an exception- The woke left, the woke right, and tribal immunity- Why taboos protect pluralistic societies- How norms fail—and how they can be restored